A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Estimating soil properties in heterogeneous land‐use patches: a Bayesian approach
10.1002/env.789.abs
Cities provide unique opportunities for integrating humans into ecology. Using data from a socio‐ecological inventory of metropolitan Phoenix, Arizona, we explore the contribution of human‐related variables to explaining observed variation in soil nitrate‐N (NO3N) and total carbon (C) concentrations across the city, agricultural fields, surrounding desert, and mixed regions. Conventional modeling approaches in such a setting would lead to examination of spatial relationships over the entire study area or on subsets of the data independently. However, the spatial relationships for NO3N and C may be different in each of these regions. Here we estimate the correlation coefficients for influential variables toward soil NO3N and C across the entire region, while at the same time accounting for potentially differing spatial patterns in each of these regions. Soil NO3N shows markedly greater spatial autocorrelation in the desert regions, while the soil C shows varying amounts of spatial relationships in the different regions. Copyright © 2006 John Wiley & Sons, Ltd.
Estimating soil properties in heterogeneous land‐use patches: a Bayesian approach
10.1002/env.789.abs
Cities provide unique opportunities for integrating humans into ecology. Using data from a socio‐ecological inventory of metropolitan Phoenix, Arizona, we explore the contribution of human‐related variables to explaining observed variation in soil nitrate‐N (NO3N) and total carbon (C) concentrations across the city, agricultural fields, surrounding desert, and mixed regions. Conventional modeling approaches in such a setting would lead to examination of spatial relationships over the entire study area or on subsets of the data independently. However, the spatial relationships for NO3N and C may be different in each of these regions. Here we estimate the correlation coefficients for influential variables toward soil NO3N and C across the entire region, while at the same time accounting for potentially differing spatial patterns in each of these regions. Soil NO3N shows markedly greater spatial autocorrelation in the desert regions, while the soil C shows varying amounts of spatial relationships in the different regions. Copyright © 2006 John Wiley & Sons, Ltd.
Estimating soil properties in heterogeneous land‐use patches: a Bayesian approach
Oleson, Jacob J. (author) / Hope, Diane (author) / Gries, Corinna (author) / Kaye, Jason (author)
Environmetrics ; 17 ; 517-525
2006-08-01
9 pages
Article (Journal)
Electronic Resource
English
Estimating soil properties in heterogeneous land-use patches: a Bayesian approach
| Online Contents | 2006